Student Talks

Abstract: The era of vision-language models (VLMs) trained on large web-scale datasets challenges conventional formulations of “open-world" perception. In this work, we revisit the task of few-shot object detection (FSOD) in the context of recent foundational VLMs. First, we point out that zero-shot VLMs such as GroundingDINO significantly outperform state-of-the-art few-shot detectors (48 vs. 33 AP) [...]

Abstract: The inability to explore environments efficiently makes online RL sample-inefficient. Most existing works tackle this problem in a setting devoid of prior information. However, additional affordances may often be cheaply available at the time of training. These affordances include small quantities of demo data, simulators that can reset to arbitrary states and domain specific [...]

Abstract: In recent years there has been a rapid development in agile robots capable of operating at their limits in dynamic environments. Autonomous racing and recent developments in it also spurred by competitions such as the Indy Autonomous Challenge, A2RL, and F1Tenth have shown how modern autonomous control algorithms are capable of operating racecars at [...]

Abstract: Robotic manipulation is an important area of research to improve the level of efficiency and autonomy in manufacturing processes. Due to the high precision and repeatability of industrial robot arms, robotic manufacturing tasks are dominated by simple pick, place, and peg insertion actions performed in a highly structured environment. Lego blocks are an excellent [...]

Abstract: Quadruped robots offer a versatile solution for navigating complex terrain, making them valuable for applications such as industrial automation or search and rescue. Although quadrupeds are more complex than bipeds, they are easier to balance and control and require fewer joints to actuate compared to hexapods. Traditional quadruped designs, however, often feature complex leg [...]

Abstract: This work investigates a constrained inverse kinematic (IK) problem that seeks a feasible configuration of an articulated robot under various constraints such as joint limits and obstacle collision avoidance. Due to the high-dimensionality and complex constraints, this problem is often solved numerically via iterative local optimization. Classic local optimization methods take joint angles as [...]

Abstract: Achieving human and animal-level agility has been a long-standing goal in robotics research. Recent advancements in numerical optimization and machine learning have pushed legged systems to greater capabilities than ever before, enabling black flips, parkour, and manipulation of heavy objects. Despite these exciting developments, this thesis identifies two key limitations of current legged robot [...]

Abstract: Model predictive control (MPC) is a powerful tool for controlling highly dynamic robotic systems subject to complex constraints. However, it is computationally expensive and often requires a large memory footprint. Larger robotic systems are capable of carrying and powering sophisticated computational hardware onboard. On the other hand, smaller robots typically have faster dynamics that [...]

Abstract: Legged robot hardware has become more accessible in the last ten years. However, there is still a dearth of low-cost hardware platforms that are open-source and easy to build. With recent developments in accessible manufacturing methods, such as 3D printing, it has become possible to design and manufacture parts without relying on precision machining. [...]